Instructions to use ymatty/mattytrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ymatty/mattytrained with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ymatty/mattytrained", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- dbd5def29a876a83ddb52ad1bb8e9234fdeed8d3871029b8f2b7b3feeef99d88
- Size of remote file:
- 492 MB
- SHA256:
- e7d6b529e694e4b8fd3d2748fb62d44d98a53d027b07be6fde525dc73f5f5c1e
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